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Research Article | Open Access |

Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection

Author 1: Haris Ahmad Khan Author 2: M. Salman Author 3: Sajid Hussain Author 4: Khurram Khurshid
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 3 · Published 2016 · Cited by 6

DOI: https://doi.org/10.14569/IJACSA.2016.070339

Abstract

Automated systems for road crack detection are extremely important in road maintenance for vehicle safety and traveler’s comfort. Emerging cracks in roads need to be detected and accordingly repaired as early as possible to avoid further damage thus reducing rehabilitation cost. In this paper, a robust method for Gabor filter parameters optimization for automatic road crack detection is discussed. Gabor filter has been used in previous literature for similar applications. However, there is a need for automatic selection of optimized Gabor filter parameters due to variation in texture of roads and cracks. The problem of change of background, which in fact is road texture, is addressed through a learning process by using synthetic road crack generation for Gabor filter parameter tuning. Tuned parameters are then tested on real cracks and a thorough quantitative analysis is performed for performance evaluation.

Keywords

How to Cite this Article

Khan, H. A., Salman, M., Hussain, S., & Khurshid, K. (2016). Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection. International Journal of Advanced Computer Science and Applications, 7(3). https://doi.org/10.14569/IJACSA.2016.070339

Khan, Haris Ahmad, et al.. "Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection." International Journal of Advanced Computer Science and Applications, vol. 7, no. 3, 2016, https://doi.org/10.14569/IJACSA.2016.070339.

@article{Khan2016,
  title     = {Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {3},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Haris Ahmad Khan and M. Salman and Sajid Hussain and Khurram Khurshid},
  doi       = {10.14569/IJACSA.2016.070339},
  url       = {https://doi.org/10.14569/IJACSA.2016.070339}
}

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